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Fig. 4. Comparing the threshold-based algorithm with the BDW algorithm using different FSD values on a 128 MB system. These graphs show the execution time of each application when run using the threshold-based algorithm, normalized with respect to the execution time obtained when run using the specified FSD value.

Figure 4 Comparing the threshold-based algorithm with the BDW algorithm using different FSD values on a 128 MB system. These graphs show the execution time of each application when run using the threshold-based algorithm, normalized with respect to the execution time obtained when run using the specified FSD value.

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Table II. Impact of Garbage Collection Frequency Using BDW with 64 MB System Times are in milliseconds and sizes are in MB. The row labeled “Tholds” shows the results obtained with ou1 new algorithm. This algorithm and its results are discussed in Section 4.
Table II. Impact of Garbage Collection Frequency Using BDW with 64 MB System Times are in milliseconds and sizes are in MB. The row labeled “Tholds” shows the results obtained with ou1 new algorithm. This algorithm and its results are discussed in Section 4.
Times are in milliseconds and sizes are in MB. The row labeled “Tholds” shows the results obtained with ou new algorithm. This algorithm and its results are discussed in Section 4. Table III. Impact of Garbage Collection Frequency Using BDW with 128 MB System
Times are in milliseconds and sizes are in MB. The row labeled “Tholds” shows the results obtained with ou new algorithm. This algorithm and its results are discussed in Section 4. Table III. Impact of Garbage Collection Frequency Using BDW with 128 MB System
Fig. 2. Example heap growth and garbage collection operation using thresholds.
Fig. 2. Example heap growth and garbage collection operation using thresholds.
Fig. 3. Comparing the threshold-based algorithm with the BDW algorithm using different FSD values on a 64 MB system. These graphs show the execution time of each application when run using the threshold-based algorithm, normalized with respect to the execution time obtained when run using the specified FSD value.
Fig. 3. Comparing the threshold-based algorithm with the BDW algorithm using different FSD values on a 64 MB system. These graphs show the execution time of each application when run using the threshold-based algorithm, normalized with respect to the execution time obtained when run using the specified FSD value.
ACM Transactions on Programming Languages and Systems, Vol. 28, No. 5, September 2006.
ACM Transactions on Programming Languages and Systems, Vol. 28, No. 5, September 2006.
Table VI. 64 MB ACM Transactions on Programming Languages and Systems, Vol. 28, No. 5, September 2006.
Table VI. 64 MB ACM Transactions on Programming Languages and Systems, Vol. 28, No. 5, September 2006.
Table VII. 128 MB ACM Transactions on Programming Languages and Systems, Vol. 28, No. 5, September 2006.
Table VII. 128 MB ACM Transactions on Programming Languages and Systems, Vol. 28, No. 5, September 2006.
Table IX. 128 MB ACM Transactions on Programming Languages and Systems, Vol. 28, No. 5, September 2006.
Table IX. 128 MB ACM Transactions on Programming Languages and Systems, Vol. 28, No. 5, September 2006.
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Information SystemsComputer ScienceDistributed ComputingProgramming LanguagesMemory ManagementVirtual MemoryGarbage CollectionEmbedded JavaMemory FootprintGarbage Collector
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